- Preamble
- Unpacking AutoML
- First, some context: decoding the publicity
- Industry perspectives: the business use case
- AutoML Explained
- An emerging landscape of vendors, open source, and R&D efforts
- Data Governance and AutoML: co-evolution of costs vs. risks
- Near-term scenarios: preparing for tomorrow's realities
- Outro
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Paco Nathan
2019-09-12 02:56:35
AutoML is one of the hot topics at the forefront of AI research in academia as well as R&D work in industry. Nearly all of the public cloud vendors promote some form of AutoML service. Tech unicorn companies such as Uber have also been developing AutoML services for their data platforms, which are migrating into open source. Meanwhile a flurry of tech startups promise to democratize machine learning for enterprise customers. But what does AutoML mean?
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